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Modeling and Optimization of Ultrasonic Machining Process Using a Novel Evolutionary Algorithm

Modeling and Optimization of Ultrasonic Machining Process Using a Novel Evolutionary Algorithm

Mantra Prasad Satpathy, Bharat Chandra Routara
Copyright: © 2019 |Pages: 22
ISBN13: 9781522561613|ISBN10: 1522561617|ISBN13 Softcover: 9781522587590|EISBN13: 9781522561620
DOI: 10.4018/978-1-5225-6161-3.ch007
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MLA

Satpathy, Mantra Prasad, and Bharat Chandra Routara. "Modeling and Optimization of Ultrasonic Machining Process Using a Novel Evolutionary Algorithm." Non-Conventional Machining in Modern Manufacturing Systems, edited by Kaushik Kumar, et al., IGI Global, 2019, pp. 153-174. https://doi.org/10.4018/978-1-5225-6161-3.ch007

APA

Satpathy, M. P. & Routara, B. C. (2019). Modeling and Optimization of Ultrasonic Machining Process Using a Novel Evolutionary Algorithm. In K. Kumar, N. Kumari, & J. Davim (Eds.), Non-Conventional Machining in Modern Manufacturing Systems (pp. 153-174). IGI Global. https://doi.org/10.4018/978-1-5225-6161-3.ch007

Chicago

Satpathy, Mantra Prasad, and Bharat Chandra Routara. "Modeling and Optimization of Ultrasonic Machining Process Using a Novel Evolutionary Algorithm." In Non-Conventional Machining in Modern Manufacturing Systems, edited by Kaushik Kumar, Nisha Kumari, and J. Paulo Davim, 153-174. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-6161-3.ch007

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Abstract

Ultrasonic machining (USM) is one of the non-conventional techniques for machining of hard and brittle materials like glass, ceramics, and ceramic matrix composites. The objective of the study includes the investigation of material removal rate (MRR), hole oversize (HOS), and circularity of holes (COH) during USM of soda lime glass and finding out the optimal parametric condition by an evolutionary algorithm. Taguchi philosophy was employed to carry out experiments using the process parameters such as power rating, abrasive slurry concentration, and static load. A novel optimization algorithm called imperialist competitive algorithm (ICA) was used to obtain maximum MRR and minimum HOS and COH. This algorithm is inspired by the imperialistic competition and has several advantages over other evolutionary algorithms like its simplicity, less computational time, and accuracy in predicting the results. The Technique for order of preference by similarity to ideal solution (TOPSIS) is utilized to convert these multiple performance characteristics to a single response. Moreover, the prediction outcomes of this TOPSIS integrated ICA methodology demonstrates excellent conformity with the experimental values and can be applied to solve complex problems.

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